AI Discovery Radar: measurement method and ruleset for tracking adoption of machine-readable discovery and consent routes (Technical Report v1.0)

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-15
DOI
https://doi.org/10.5281/zenodo.22769680
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

AI Discovery Radar: measurement method and ruleset for tracking adoption of machine-readable discovery and consent routes (Technical Report v1.0)

Florian Berger
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

AI Discovery Radar: measurement method and ruleset for tracking adoption of machine-readable discovery and consent routes (Technical Report v1.0)

Florian Berger
article en

Abstract

Technical report, version 1.0 (September 2026). Companion to the dataset "AI Discovery Radar — adoption measurements for machine-readable discovery and consent routes" (concept DOI 10.5281/zenodo.22178282). Adoption of machine-readable discovery and consent files for automated clients — robots.txt, llms.txt, TDMRep, agent cards, MCP manifests and others — is widely asserted and rarely counted. This report documents the method behind a monthly measurement of 34 catalogued routes on a frozen, stratified frame of 30,000 registrable domains (Tranco + Chrome UX Report; deliberately over-weighting German-, Austrian-, Swiss- and Italian-language sites). It contributes (1) a seven-state classification model with a denominator rule that separates refusal from non-adoption, (2) a two-tier, reproducible sampling design — a fixed panel for change and rotating blocks for coverage — and (3) an admission procedure for the route catalogue. Adoption here means publicly observable, syntactically valid availability of a route — deployment, not consumption. The September 2026 run illustrates the method; with two panel points under two ruleset versions, no trend is claimed. The report names its principal open question — adoption behind bot walls — and records the decision to widen the panel from 1,000 to 10,000 domains from October 2026. Measurement pitfalls (soft-404 envelopes, walls answering 404, Range-header traps, template adoption) are documented so that others can avoid them. Licence CC BY 4.0.

Zenodo (CERN European Organization for Nuclear Research)
Université Gaston Berger (SN), Berg (United States) (US)
Openalex Percentile: Top 6%
Ethics and Social Impacts of AI
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